Proteogenomic insights into the biology and treatment of pan-melanoma

Melanoma is one of the most prevalent skin cancers, with high metastatic rates and poor prognosis. Understanding its molecular pathogenesis is crucial for improving its diagnosis and treatment. Integrated analysis of multi-omics data from 207 treatment-naïve melanomas (primary-cutaneous-melanomas (CM, n = 28), primary-acral-melanomas (AM, n = 81), primary-mucosal-melanomas (MM, n = 28), metastatic-melanomas (n = 27), and nevi (n = 43)) provides insights into melanoma biology. Multivariate analysis reveals that PRKDC amplification is a prognostic molecule for melanomas. Further proteogenomic analysis combined with functional experiments reveals that the cis-effect of PRKDC amplification may lead to tumor proliferation through the activation of DNA repair and folate metabolism pathways. Proteome-based stratification of primary melanomas defines three prognosis-related subtypes, namely, the ECM subtype, angiogenesis subtype (with a high metastasis rate), and cell proliferation subtype, which provides an essential framework for the utilization of specific targeted therapies for particular melanoma subtypes. The immune classification identifies three immune subtypes. Further analysis combined with an independent anti-PD-1 treatment cohort reveals that upregulation of the MAPK7-NFKB signaling pathway may facilitate T-cell recruitment and increase the sensitivity of patients to immunotherapy. In contrast, PRKDC may reduce the sensitivity of melanoma patients to immunotherapy by promoting DNA repair in melanoma cells. These results emphasize the clinical value of multi-omics data and have the potential to improve the understanding of melanoma treatment.

A. Summary of the findings generated in this study.

Figure S2 .
Figure S2.Quality Control, and Comparison of Somatic Mutation Profiles between Four Types of Melanomas, Related to Figure 1. A. The boxplot showed SBS7a signature score in CM (n = 25), AM (n = 71), and MM (n = 28) (Wilcoxon rank test).B. The histogram showed the frequency of NF1 mutation in patients with or without SBS7a signature (n = 124) (Fisher's exact test).C. The boxplot showed the protein expression of NF1 in patients harboring NF1 mutation and WT samples in our cohort (n = 124) (Wilcoxon rank test).D. The quantification repeatability of HEK293T control samples showing the robust and accurate proteome platform (Pearson's correlation coefficients, 0.88-0.92).E. Number of proteins identified in melanoma patients.F. Dynamic range of Nevus (n = 43), CM (n = 28), AM (n = 81), MM (n = 28) and MCM (n = 27) samples.G. Correlations between mRNA and protein abundance in 4,429 mRNA-protein pairs detected in all samples.H. IHC staining CDK4 at T172, and MCM2 at S27 in melanoma tumor tissues and nevi.FFPE sections were stained for phosphorylation of CDK4 at T172 and MCM2 at S27.The scale bar indicates 100 μm.

Figure S3 .
Figure S3.PRKDC Amplification Associated with Poor Prognosis in Melanomas, Related to Figure 2. A. The boxplot indicated the mRNA expression of PRKDC between patients harbored PRKDC amplifications or not in TCGA cohort.B. The bar plot indicated the percentages of PRKDC amplifications across diverse histological types in different cohorts.C. The Kaplan-Meier curves for overall survival based on patients' PRKDC copy number alterations D. Kaplan-Meier curves for overall survival based on patients grouped by genomic alterations in our cohort.E. The relationship between the protein expression of MTSS1 and GSVA scores of GO process actin cytoskeleton organization.F. The interactions among proteins enriched in actin cytoskeleton organization.Proteins were colorcoded based on their correlation with MTSS1.G.The volcano plot indicates the relationship between drugs' sensitivity and protein expression of PRKDC.H.The boxplot indicates the protein expression of PRKDC across cell lines with different PRKDC expression levels.I. Dose-response curves of 5-FU were determined on day 2 after inhibitors were added to cell lines.The data represent the mean values ± SD (n = 3) (left); The violin plot shows the IC50 scores.The data represent the mean values ± SD (n = 3) (right).J-K The proliferation of the cell lines with different PRKDC expression levels, under 5-FU treatment (K)or not (J).

Figure S4 .
Figure S4.PRKDC Amplification Contributed to Expression Alterations of Proteins in Folate Metabolism, Related to Figure 3. A. The workflow showed the sample collection for mass spectrum analysis (control HMCB cells, scramble shRNA control HMCB cells, PRKDC-OE HMCB cells, and PRKDC-KD HMCB cells).B. The violin plots indicated the expression patterns of PRKDC across cells with different treatments.C. The violin plots indicated the expression patterns of MXD3/S57 across cells with different treatments.

Figure S6 .
Figure S6.Consensus Clustering Analysis Conducted in Melanomas, Related to Figure 4. A-B.Heatmap of consensus cluster plus, cophenetic correlation coefficient and average silhouette width plots.The input is the quantile-normalized iBAQ intensity matrix of the top 1000 most variant proteins across 137 tumor samples.Based on a visual inspection of the hierarchical clustering and the profiles of the cophenetic correlation coefficient and average silhouette width for solutions with 2 to 5 clusters, we considered K = 3 to be the preferred solution (as indicated by black triangles) and used this scheme to arrange the samples shown in Figure4 and TableS4.(yielding the three clusters highlighted in green,

Figure S7 .
Figure S7.ROCK2 Amplification Associated with Metastasis in Melanomas, Related to Figure 5. A. The heatmap showed the protein expression of kinases (ROCK2), and abundance of phosphosites enriched in angiogenesis.The Spearman's correlation coefficients between ROCK2's protein expression and abundance of phosphosites are calculated and display on the right panel, with p values displayed in log10 scale.B. The heatmap showed the abundance of the phosphosite HMGB1/S100 (TF), and the expression pattern of the target gene (TG) of HMGB1.The Spearman's correlation coefficients between the abundance of phosphosites HMGB1/S100 and expression of TGs are calculated and display on the left panel, with p values displayed in log10 scale.C. The boxplot indicates the expression level ROCK2 across OE-Control-A375, OE-ROCK2-A375, KD-Control-A375, and ROCK2-KD-A375.D. The boxplot indicates the phosphorylation of HMGB1 at S100 across OE-Control-A375, OE-ROCK2-A375, KD-Control-A375, and ROCK2-KD-A375.

Figure S8 .
Figure S8.Immune-Based Subtyping of Melanomas, Related to Figure 6.A-B.Heatmap of consensus cluster plus, cophenetic correlation coefficient and average silhouette width plots.The input is the xCell score matrix.Based on a visual inspection of the hierarchical clustering and the profiles of the cophenetic correlation coefficient and average silhouette width for solutions with 2 to 5 clusters, we considered K = 3 to be the preferred solution (as indicated by black triangles) and used this scheme to arrange the samples shown in Figure6 and Table S6.(yielding the three clusters highlighted in green, orange and purple).

Figure S9 .
Figure S9.The Refined Subtype including the Information of both the Immune and Proteomic Subtype and Correlated with OS. A. Kaplan-Meier curves for overall survival (OS) among five subtypes (p-value based on the logrank test).B. Heatmap illustrating frequencies of PRKDC amplification, CDK4 amplification, and ROCK2 amplification, and xCell immune signatures (n = 75).C. Plots showed frequencies of PRKDC amplification, CDK4 amplification, and ROCK2 amplification.D. Plots showed protein expression of PRKDC, CDK4, and ROCK2 among five subtypes.E. Heatmap illustrating xCell score of CD8+ T-cells and Tgd cells, and mRNA expression of CD8A, HLA-A, HLA-B, HLA-C, CD274 and IL17D.F. The table represented Gene Ontology bioprocesses that were significantly altered in HC4 and HC5.G.The bar plots showed GO terms enriched by phosphoproteins which showed diverse expression patterns in HC4 and HC5.H. Kaplan-Meier curves for overall survival (OS) based on the kinase activity of AKT3 (p-value based on the log-rank test).I. Spearman-rank correlation of the AKT3's kinase activity and xCell score of Tgd cells and the ssGSEA score of cell cycle.J. Heatmap illustrated the protein expression of cell cycle related proteins in HC4 and HC5.

Figure S10 .
Figure S10.Summary of the findings generated in this study.